Matlab Code for Neuro Fuzzy Based Image Fusion Using Image Processing
ABSTRACT
Image Fusion is a process of combining relevant information from a set of images into a single image. The resultant fused image will be more informative and complete than any of the input images. The aim of image fusion is to integrate complementary as well as redundant information from multiple images to create a fused image output. Therefore the new image generated is more informative and accurate than any of the individual source. Multisensor data fusion has become a discipline which demands more general formal solutions to a number of application cases. Several situations in image processing require both high spatial and high spectral information in a single image. This is important in remote sensing. However, the instruments are not capable of providing such information either by design or because of observational constraints. One possible solution for this is data fusion. Image fusion can be broadly defined as the process of combing multiple input images or some of their features into a single image without the introduction of distortion or loss of information. The aim of image fusion is to integrate complementary as well as redundant information from multiple images to create a fused image output. Therefore, the new image generated should contain a more accurate description of the scene than any of the individual source images and is more suitable for human visual and machine perception or further image processing and analysis tasks. For medical image fusion, the fusion of images can often lead to additional clinical information not apparent in the separate images. Another advantage is that it can reduce the storage cost by storing just the single fused image instead of multisource images.
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